References
- Artola A, Singer W. Long term depression of excitatory synaptic transmission and its relationship to long term potentiation. Trends Neurosci. 1993; 16: 480–7
- Atick J J, Redlich A N. What does the retina know about natural scenes. Neural Comput. 1992; 4: 196–211
- Atick J J, Redlich A N. Convergent algorithm for sensory receptive field development. Neural Comput. 1993; 5: 45–60
- Barlow H B. Unsupervised learning. Neural Comput. 1989; 1: 295–311
- Barlow H B, Pettingrew J D. Lack of specificity in the visual cortex of yong kittens. J. Physiol. 1971; 218: 98–100
- Bear M F, Malenka R C. Synaptic plasticity: Ltp and ltd. Curr. Opinion Neurobiol. 1994; 4: 389–99
- Bialek W, Ruderman D L, Zee A. Optimal sampling of natural images: a design principle for the visual system?. Neural Information Processing 3, J Moody, R Lippman, D Touretzkey. Morgan Kaufmann, San Mateo, CA 1991; 363–9
- Blakemore C, Van-Sluyters R R. Inate and environmental factors in the development of the kitten's visual cortex. J. Physiol. 1975; 248: 663–716
- Field D J. Relations between the statistics of natural images and the response properties of cortical cells. J. Opt. Soc. Am. A 1987; 4: 2379–94
- Frégnac Y, Thorpe S, Bienenstock E L. Cellular analogs of visual cortical epigenesis. I. Plasticity of orientation selectivity. J. Neurosci. 1992; 12: 1280–1300
- Hancock P J, Baddeley R J, Smith L S. The principal components of natural images. Network: Comput. Neural Syst. 1992; 3: 61–70
- Hebb D O. The Organization of Behavior. Wiley, New York 1949
- Imbert M, Buisseret P. Receptive field characteristics and plastic properties of visual cortical cells in kittens reared with or without visual experience. Exp. Brain Res. 1975; 22: 25–36
- Jackson J D. Classical Electrodynamics. Wiley, New York 1975
- Linsker R. From basic network principles to neural architecture. Proc. Natl Acad. Sci. USA 1986; 83: 7508–12; 8390–4; 8779–83
- Linsker R. Self-organization in a perceptual network. Computer (March 1988) 1988; 105–117
- Liu Y, Shouval H. Localized principal components of natural images—an analytic solution. Network: Comput. Neural Syst. 1994; 5: 317–25
- Miller K D, MacKay D J C. The role of constraints in Hebbian learning. Neural Comput. 1994; 6: 98–124
- Miller K D. A model for the development of simple cell receptive fields and the ordered arrangement of orientation columns through activity-dependent competition between on- and off-center inputs. J. Neurosci. 1994; 14: 409–41
- Miller K D, Keller J B, Striker M P. Ocular dominance column development: analysis and simulation. Science 1989; 245: 605–15
- Nass M N, Cooper L N. A theory for the development of feature detecting cells in visual cortex. Biol. Cybern. 1975; 19: 1–18
- Oja E. A simplified neuron model as a principal component analyzer. J. Math. Biol. 1982; 15: 267–73
- Ruderman D L. The statistics of natural images. Network: Comput. Neural Syst. 1994; 5: 517–48
- Ruderman D L. Origins of scaling in natural images. 1996, to be published
- Ruderman D L, Bialek W. Statistics of natural images: scaling in the woods. Advances in Neural Information Processing Systems 6, G Tesauro, J D Cowan, J Alspector. Morgan Kaufman, San Mateo, CA 1994
- Sanger T D. Optimal unsupervised learning in a single-layer linear feedforward neural network. Neural Networks 1989; 2: 459–73
- von der Malsburg Ch. Self-organization of orientation sensitive cells in striate cortex. Kybernetik 1973; 14: 85–100